Metagenome-assembled genome: ERP113451_co3_278
This sample represents a Third Party Annotation (TPA) Metagenome-assembled genome assembled from the metagenomic runs ERR3094294,ERR3094296 of study ERP113451.
ENA first public
2024-12-11
INSDC center name
CMR
INSDC status
public
Submitter Id
ERP113451_co3_278
assembly quality
Many fragments with little to no review of assembly other than reporting of standard assembly statistics
assembly software
metaSPAdes;3.15.4;default
binning parameters
coverage and kmer
binning software
MetaBAT;2.15;default
broad-scale environmental context
aquatic
collection date
not provided
completeness score
90.94
completeness software
CheckM2;1.0.2;default
contamination score
0.52
environmental medium
aquatic
geographic location (country and/or sea)
not provided
geographic location (latitude)
not provided
geographic location (longitude)
not provided
investigation type
metagenome-assembled genome
isolation_source
metagenome
local environmental context
metagenome
metagenomic source
metagenome
project name
Total microbial communities were collected from an old gasworks site over a year (May 2016 - May 2017). Six sampling stations were studied. Fourteen total metagenomes, viromes and 16S rRNA gene amplicon datasets were generated using Illumina Sequencing. For details about this study, please refer to: Costeira R, Doherty R, Allen CCR, Larkin MJ, Kulakov LA. Analysis of viral and bacterial communities in groundwater associated with contaminated land. Sci Total Environ 2019 656:1413–26. doi:10.1016/j.scitotenv.2018.11.429.This work was supported by the European Union's Horizon 2020 - Research and Innovation Framework Programme under the Marie Sklodowska-Curie grant agree-ment No. 643087 REMEDIATE (Improved decision-making in contaminated land site investigation and risk assessment).
sample derived from
SAMEA5243711,SAMEA5243713
sample name
ERP113451_co3_278
scientific_name
uncultured Candidatus Saccharimonas sp.
sequencing method
Illumina HiSeq 4000,Illumina HiSeq 2000
taxonomic identity marker
multi-marker approach